The Cognitive Revolution: The Next Wave

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The Cognitive Revolution: The Next Wave (By Leda Cosmides)

Scientific progress sometimes comes not from new methods, but from new concepts, new ways of framing old problems. The cognitive revolution is a wonderful example of this. The language of information processing and computation provided a new way of thinking about what the brain does. Recently, though, I was forcefully reminded that this revolution is not yet complete. It’s not just a matter of explaining its implications to the scientific community at large. We psychologists have barely begun to tap the potential of the cognitive revolution for transforming our own field.

What occasioned these thoughts? Recently, I had to explain to a panel of eminent biomedical scientists — most were pharmacologists, biophysicists, chemists, molecular biologists, and physiologists — what I spend my time doing and why they should care. You all know the problem this poses. No one thinks that having a heart gives them special insight into how it operates. But it is seductive to think that having a brain gives us each special insight into its internal workings — a problem made worse by the theory of mind mechanism, which generates the intuition that the causes of behavior are simple: our beliefs and desires.

So I started by connecting what I do to what they do: We all study organ systems. Each organ in the body evolved to serve a function: The heart was designed by natural selection to pump blood, the intestines to digest, the liver to detoxify poisons. The brain is also an organ, but its evolved function is not primarily metabolic. Its evolved function is to extract information from the (internal and external) environment and use that information to generate behavior and regulate physiology. From this perspective, the brain is a computational device — a physical system that was designed to process information. So to describe the brain’s operation in a way that captures its evolved function, you need to think of it as composed of programs that process information. This requires theories expressed in information-processing (computational) terms. I explained that these are not the poor relations of neural or molecular theories: Neural circuits were retained or discarded by selection because of the computations they created. This means the information processing level of description is essential for knowing what the neural circuits are doing, and will never be made obsolete by progress in molecular biology and neuroscience. This powerful insight turned the study of perception, attention, memory, reasoning, and learning into a real science. But, there are so many topics to which it has barely been applied!

So far, the cognitive sciences have told us a reasonable amount about the computations that go on in our brains when we are learning mathematics, reading, or reflecting on our day — so-called “higher-level” or “cold” cognition. But they have told us very little about the automatic, spontaneous, and largely nonconscious computations that go on in our brains when we are angry, grieving, falling in love, jealous, feeling guilty, helping friends, or soothing a child, let alone the computations that give rise to family love and conflict, the desire to be part of an “us” or to compete with “them,” the impulse to contribute to the common good or to punish those who don’t. Clinical psychologists deal with phenomena like these on a daily basis. But how many cognitive scientists study these topics?